Bibliographic record
Abstract
PURPOSE OF REVIEW: To review the current literature of childhood primary and secondary central nervous system (CNS) vasculitis and to evaluate the growing differential diagnosis of inflammatory and noninflammatory brain diseases. RECENT FINDINGS: Primary angiitis of the central nervous system in children (cPACNS) is a reversible cause of severe neurological deficits and/or psychiatric symptoms. This disease is classified into subtypes based on distinct clinical and radiological features, treatment strategies, and disease trajectories. Also, the increased diagnostic yield from elective brain biopsies in children has improved our ability to diagnose angiography-negative cPACNS. Over the past few years, the differential diagnosis for cPACNS has rapidly expanded due to the characterization of novel inflammatory and noninflammatory brain diseases. Specifically, vasoconstrictive disorders and neuronal antibody-associated conditions have now been described in children and have overlapping clinical features with cPACNS. SUMMARY: This review summarizes the recent data on diagnosis, treatment, and prognosis of cPACNS. It also addresses the evolving differential diagnosis for CNS vasculitis. Our improved understanding of these disorders allows a tailored diagnostic approach leading to rapid diagnosis and initiation of therapy in these potentially reversible conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".